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AI/ML Full Stack Engineer Job Opening In Washington Highlands District of Columbia – Now Hiring Mindlance


Job description

Title: AI/ML Full Stack Engineer

Duration: 9 Months - Long Term

Location: Washington, DC 20433

Hybrid Onsite: 4 Days per week onsite from Day1




Role and responsibilities:


  • Developing AI models: Building and fine-tuning machine learning models, including specialized ones like large language models (LLMs), to solve development challenges.


  • Engineering cloud applications: Designing and building cloud-native data and AI tools and ensuring they are scalable, secure, and performant.

    Client frequently uses cloud platforms like Azure, GCP, or AWS.


  • Building user interfaces: Developing the front-end user experience, including interactive data and knowledge dashboards.


  • Managing data infrastructure: Handling large, complex datasets, including data sourcing, cleaning, and preparation for model training.


  • Implementing best practices: Coordinating the technical work of data teams by conducting code reviews, implementing MLOps strategies, and ensuring ethical AI use .

  • Working with stakeholders: Collaborating with internal teams and external partners to gather requirements and present AI-driven solutions.





Required skills and qualifications:

To succeed in this position, you need a strong technical foundation and experience with both the AI and software development lifecycles.




  • Education: A master's degree or higher in a relevant field, such as Computer Science, Data Science, or Artificial Intelligence, is typically required.


  • Experience: A minimum of 7-10 years of professional experience in a related role is often requested.

    This should include hands-on experience in AI engineering and cloud-native application development.


  • Programming languages: Proficiency in Python is essential, along with experience using AI/ML frameworks like TensorFlow, PyTorch, or Scikit-learn.

    Strong skills in JavaScript/TypeScript and front-end frameworks like React are also necessary for full-stack roles.


  • Cloud platforms: Expertise in cloud platforms (Azure, AWS, or GCP) and related services is critical for deploying and managing AI solutions.


  • Databases: Knowledge of both relational and NoSQL databases is required.


  • Other technical skills: Experience with containerization (Docker, Kubernetes), version control (Git), and CI/CD pipelines is a major asset.


  • Soft skills: Excellent communication, problem-solving, and collaboration skills are vital for working in interdisciplinary and multicultural teams.




Mindlance is an Equal Opportunity Employer and does not discriminate in employment on the basis of Minority/Gender/Disability/Religion/LGBTQI/Age/Veterans.


Required Skill Profession

Other General


  • Job Details

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Unlock Your AI ML Potential: Insight & Career Growth Guide


Real-time AI ML Jobs Trends (Graphical Representation)

Explore profound insights with Expertini's real-time, in-depth analysis, showcased through the graph here. Uncover the dynamic job market trends for AI ML in Washington Highlands, District of Columbia, United States, highlighting market share and opportunities for professionals in AI ML roles.

23130 Jobs in United States
23130
493 Jobs in Washington Highlands, District Of Columbia
493
Download Ai Ml Jobs Trends in Washington Highlands, District Of Columbia and United States

Are You Looking for AI/ML Full Stack Engineer Job?

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The Work Culture

An organization's rules and standards set how people should be treated in the office and how different situations should be handled. The work culture at Mindlance adheres to the cultural norms as outlined by Expertini.

The fundamental ethical values are:

1. Independence

2. Loyalty

3. Impartiapty

4. Integrity

5. Accountabipty

6. Respect for human rights

7. Obeying United States laws and regulations

What Is the Average Salary Range for AI/ML Full Stack Engineer Positions?

The average salary range for a varies, but the pay scale is rated "Standard" in Washington Highlands District of Columbia. Salary levels may vary depending on your industry, experience, and skills. It's essential to research and negotiate effectively. We advise reading the full job specification before proceeding with the application to understand the salary package.

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Key qualifications for AI/ML Full Stack Engineer typically include Other General and a list of qualifications and expertise as mentioned in the job specification. The generic skills are mostly outlined by the . Be sure to check the specific job listing for detailed requirements and qualifications.

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Interview Tips for AI/ML Full Stack Engineer Job Success

Mindlance interview tips for AI/ML Full Stack Engineer

Here are some tips to help you prepare for and ace your AI/ML Full Stack Engineer job interview:

Before the Interview:

Research: Learn about the Mindlance's mission, values, products, and the specific job requirements and get further information about

Other Openings

Practice: Prepare answers to common interview questions and rehearse using the STAR method (Situation, Task, Action, Result) to showcase your skills and experiences.

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Be Punctual: Arrive on time to demonstrate professionalism and respect.

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Follow Up: Send a thank-you email to the interviewer within 24 hours.

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Final Thought:

To prepare for your AI/ML Full Stack Engineer interview at Mindlance, research the company, understand the job requirements, and practice common interview questions.

Highlight your leadership skills, achievements, and strategic thinking abilities. Be prepared to discuss your experience with HR, including your approach to meeting targets as a team player. Additionally, review the Mindlance's products or services and be prepared to discuss how you can contribute to their success.

By following these tips, you can increase your chances of making a positive impression and landing the job!

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